Summary

Summary {data-width=650}

Manhattan plot

manhattan_plot

manhattan_plot

QQ plot

qq_plot

qq_plot

AF plot

af_plot

af_plot

P-Z plot

pz_plot

pz_plot

beta_std plot

beta_std_plot

beta_std_plot

Metadata

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}
 

LDSC

*********************************************************************
* LD Score Regression (LDSC)
* Version 1.0.1
* (C) 2014-2019 Brendan Bulik-Sullivan and Hilary Finucane
* Broad Institute of MIT and Harvard / MIT Department of Mathematics
* GNU General Public License v3
*********************************************************************
Call: 
./ldsc.py \
--h2 /mnt/storage/private/mrcieu/research/scratch/IGD/data/dev/ukb-d-import/processed/ukb-d-30640_raw/ukb-d-30640_raw.vcf.gz \
--ref-ld-chr /mnt/storage/private/mrcieu/research/scratch/IGD/data/dev/reference/eur_w_ld_chr/ \
--out /mnt/storage/private/mrcieu/research/scratch/IGD/data/dev/ukb-d-import/processed/ukb-d-30640_raw/ldsc.txt \
--w-ld-chr /mnt/storage/private/mrcieu/research/scratch/IGD/data/dev/reference/eur_w_ld_chr/ 

Beginning analysis at Mon Nov 25 14:59:25 2019
Reading summary statistics from /mnt/storage/private/mrcieu/research/scratch/IGD/data/dev/ukb-d-import/processed/ukb-d-30640_raw/ukb-d-30640_raw.vcf.gz ...
Read summary statistics for 13585957 SNPs.
Dropped 12711 SNPs with duplicated rs numbers.
Reading reference panel LD Score from /mnt/storage/private/mrcieu/research/scratch/IGD/data/dev/reference/eur_w_ld_chr/[1-22] ...
Read reference panel LD Scores for 1290028 SNPs.
Removing partitioned LD Scores with zero variance.
Reading regression weight LD Score from /mnt/storage/private/mrcieu/research/scratch/IGD/data/dev/reference/eur_w_ld_chr/[1-22] ...
Read regression weight LD Scores for 1290028 SNPs.
After merging with reference panel LD, 1283503 SNPs remain.
After merging with regression SNP LD, 1283503 SNPs remain.
Using two-step estimator with cutoff at 30.
Total Observed scale h2: 0.1469 (0.0424)
Lambda GC: 1.3162
Mean Chi^2: 1.8975
Intercept: 1.0861 (0.0173)
Ratio: 0.096 (0.0192)
Analysis finished at Mon Nov 25 15:02:14 2019
Total time elapsed: 2.0m:49.06s

QC metrics

Metrics

Metrics

{
    "af_correlation": 0.9521,
    "inflation_factor": 1.2014,
    "mean_EFFECT": 1.4852e-06,
    "n": 342590,
    "n_snps": 13585957,
    "n_clumped_hits": 173,
    "n_p_sig": 35034,
    "n_mono": 0,
    "n_ns": 1251778,
    "n_mac": 0,
    "is_snpid_unique": false,
    "n_miss_EFFECT": 0,
    "n_miss_SE": 0,
    "n_miss_PVAL": 0,
    "n_miss_AF": 0,
    "n_miss_AF_reference": 569171,
    "n_est": 343911.0675,
    "ratio_se_n": 1.0019,
    "mean_diff": 4.8226e-06,
    "ratio_diff": 511.2522,
    "sd_y_est1": 0.2347,
    "sd_y_est2": 0.2351,
    "r2_sum1": 0.0039,
    "r2_sum2": 0.071,
    "r2_sum3": 0.0707,
    "r2_sum4": 0.0708,
    "ldsc_nsnp_merge_refpanel_ld": 1283503,
    "ldsc_nsnp_merge_regression_ld": 1283503,
    "ldsc_observed_scale_h2_beta": 0.1469,
    "ldsc_observed_scale_h2_se": 0.0424,
    "ldsc_intercept_beta": 1.0861,
    "ldsc_intercept_se": 0.0173,
    "ldsc_lambda_gc": 1.3162,
    "ldsc_mean_chisq": 1.8975,
    "ldsc_ratio": 0.0959
}
 

Flags

name value
af_correlation FALSE
inflation_factor TRUE
n FALSE
is_snpid_non_unique TRUE
mean_EFFECT_nonfinite FALSE
mean_EFFECT_05 FALSE
mean_EFFECT_01 FALSE
mean_chisq TRUE
n_p_sig TRUE
miss_EFFECT FALSE
miss_SE FALSE
miss_PVAL FALSE
ldsc_ratio FALSE
ldsc_intercept_beta FALSE
n_clumped_hits FALSE
r2_sum1 FALSE
r2_sum2 FALSE
r2_sum3 FALSE
r2_sum4 FALSE

Definitions

General metrics

  • af_correlation: Correlation coefficient between AF and AF_reference.
  • inflation_factor (lambda): Genomic inflation factor.
  • mean_EFFECT: Mean of EFFECT size.
  • n: Maximum value of reported sample size across all SNPs, \(n\).
  • n_clumped_hits: Number of clumped hits.
  • n_snps: Number of SNPs
  • n_p_sig: Number of SNPs with pvalue below 5e-8.
  • n_mono: Number of monomorphic (MAF == 1 or MAF == 0) SNPs.
  • n_ns: Number of SNPs with nonsense values:
    • alleles other than A, C, G or T.
    • P-values < 0 or > 1.
    • negative or infinite standard errors (<= 0 or = Infinity).
    • infinite beta estimates or allele frequencies < 0 or > 1.
  • n_mac: Number of cases where MAC (\(2 \times N \times MAF\)) is less than 6.
  • is_snpid_unique: true if the combination of ID REF ALT is unique and therefore no duplication in snpid.
  • n_miss_<*>: Number of NA observations for <*> column.

se_n metrics

  • n_est: Estimated sample size value, \(\widehat{n}\).
  • ratio_se_n: \(\texttt{ratio_se_n} = \frac{\sqrt{\widehat{n}}}{\sqrt{n}}\). We expect ratio_se_n to be 1. When it is not 1, it implies that the trait did not have a variance of 1, the reported sample size is wrong, or that the SNP-level effective sample sizes differ markedly from the reported sample size.
  • mean_diff: \(\texttt{mean_diff} = \sum_{j} \frac{\widehat{\beta_j^{std}} - \beta_j}{\texttt{n_snps}}\), mean difference between the standardised beta, predicted from P-values, and the observed beta. The difference should be very close to zero if trait has a variance of 1.
    • \(\widehat{\beta_j^{std}} = \sqrt{\frac{{z}_j^2 / ({z}_j^2 + n -2)}{2 \times {MAF}_j \times (1 - {MAF}_j)}} \times sign({z}_j)\),
    • \({z}_j = \frac{\beta_j}{{se}_j}\),
    • and \(\beta_j\) is the reported effect size.
  • ratio_diff: \(\texttt{ratio_diff} = |\frac{\texttt{mean_diff}}{\texttt{mean_diff2}}|\), absolute ratio between the mean of diff and the mean of diff2 (expected difference between the standardised beta predicted from P-values, and the standardised beta derived from the observed beta divided by the predicted SD; NOT reported). The ratio should be close to 1. If different from 1, then implies that the betas are not in a standard deviation scale.
    • \(\texttt{mean_diff2} = \sum_{j} \frac{\widehat{\beta_j^{std}} - \beta^{\prime}_j}{\texttt{n_snps}}\)
    • \(\beta^{\prime}_j = \frac{\beta_j}{\widehat{\texttt{sd2}}_{y}}\)
  • sd_y_est1: The standard deviation for the trait inferred from the reported sample size, median standard errors for the SNP-trait assocations and SNP variances.
    • \(\widehat{\texttt{sd1}}_{y} = \frac{\sqrt{n} \times median({se}_j)}{C}\),
    • \(C = median(\frac{1}{\sqrt{2 \times {MAF}_j \times (1 - {MAF}_j)}})\),
    • and \({se}_j\) is the reported standard error.
  • sd_y_est2: The standard deviation for the trait inferred from the reported sample size, Z statistics for the SNP-trait effects (beta/se) and allele frequency.
    • \(\widehat{\texttt{sd2}}_{y} = median(\widehat{sd_j})\),
    • \(\widehat{sd_j} = \frac{\beta_j}{\widehat{\beta_j^{std}}}\),

r2 metrics

Sum of variance explained, calculated from the clumped top hits sample.

  • r2_sum<*>: r2 statistics under various assumptions
    • 1: \(r^2 = \sum_j{\frac{2 \times \beta_j^2 \times {MAF}_j \times (1 - {MAF}_j)}{\texttt{var1}}}\), \(\texttt{var1} = 1\).
    • 2: \(r^2 = \sum_j{\frac{2 \times \beta_j^2 \times {MAF}_j \times (1 - {MAF}_j)}{\texttt{var2}}}\), \(\texttt{var2} = {\widehat{\texttt{sd1}}_{y}}^2\),
    • 3: \(r^2 = \sum_j{\frac{2 \times \beta_j^2 \times {MAF}_j \times (1 - {MAF}_j)}{\texttt{var3}}}\), \(\texttt{var3} = {\widehat{\texttt{sd2}}_{y}}^2\),
    • 4: \(r^2 = \sum_j{\frac{F_j}{F_j + n - 2}}\), \(F = \frac{\beta_j^2}{{se}_j^2}\).

LDSC metrics

Metrics from LD regression

  • ldsc_nsnp_merge_refpanel_ld: Number of remaining SNPs after merging with reference panel LD.
  • ldsc_nsnp_merge_regression_ld: Number of remaining SNPs after merging with regression SNP LD.
  • ldsc_observed_scale_h2_{beta,se} Coefficient value and SE for total observed scale h2.
  • ldsc_intercept_{beta,se}: Coefficient value and SE for intercept. Intercept is expected to be 1.
  • ldsc_lambda_gc: Lambda GC statistics.
  • ldsc_mean_chisq: Mean \(\chi^2\) statistics.
  • ldsc_ratio: \(\frac{\texttt{ldsc_intercept_beta} - 1}{\texttt{ldsc_mean_chisq} - 1}\), the proportion of the inflation in the mean \(\chi^2\) that the LD Score regression intercepts ascribes to causes other than polygenic heritability. The value of ratio should be close to zero, though in practice values of 0.1-0.2 are not uncommon, probably due to sample/reference LD Score mismatch or model misspecification (e.g., low LD variants have slightly higher \(h^2\) per SNP).

Flags

When a metric needs attention, the flag should return TRUE.

  • af_correlation: abs(af_correlation) < 0.7.
  • inflation_factor: inflation_factor > 1.2.
  • n: n (max reported sample size) < 10000.
  • is_snpid_non_unique: NOT is_snpid_unique.
  • mean_EFFECT_nonfinite: mean(EFFECT) is NA, NaN, or Inf.
  • mean_EFFECT_05: abs(mean(EFFECT)) > 0.5.
  • mean_EFFECT_01: abs(mean(EFFECT)) > 0.1.
  • mean_chisq: ldsc_mean_chisq > 1.3 or ldsc_mean_chisq < 0.7.
  • n_p_sig: n_p_sig > 1000.
  • miss_<*>: n_miss_<*> / n_snps > 0.01.
  • ldsc_ratio: ldsc_ratio > 0.5
  • ldsc_intercept_beta: ldsc_intercept_beta > 1.5
  • n_clumped_hits: n_clumped_hits > 1000
  • r2_sum<*>: r2_sum<*> > 0.5

Plots

  • Manhattan plot
    • Red line: \(-log_{10}^{5 \times 10^{-8}}\)
    • Blue line: \(-log_{10}^{5 \times 10^{-5}}\)
  • QQ plot
  • AF plot
  • P-Z plot
  • beta_std plot: Scatter plot between \(\widehat{\beta_j^{std}}\) and \(\beta_j\)

Diagnostics

Details

Summary stats

skim_type skim_variable n_missing complete_rate character.min character.max character.empty character.n_unique character.whitespace numeric.mean numeric.sd numeric.p0 numeric.p25 numeric.p50 numeric.p75 numeric.p100 numeric.hist
character ID 0 1.0000000 3 94 0 13573910 0 NA NA NA NA NA NA NA NA
character REF 0 1.0000000 1 100 0 57082 0 NA NA NA NA NA NA NA NA
character ALT 0 1.0000000 1 342 0 33337 0 NA NA NA NA NA NA NA NA
numeric CHROM 0 1.0000000 NA NA NA NA NA 9.051233e+00 6.184960e+00 1.0000e+00 4.000000e+00 8.000000e+00 1.300000e+01 2.300000e+01 ▇▅▅▂▂
numeric POS 0 1.0000000 NA NA NA NA NA 7.902570e+07 5.591520e+07 3.0200e+02 3.293104e+07 7.013916e+07 1.148602e+08 2.492309e+08 ▇▆▅▂▁
numeric EFFECT 0 1.0000000 NA NA NA NA NA 1.500000e-06 3.470200e-03 -1.5002e-01 -9.859000e-04 -1.300000e-06 9.884000e-04 8.050300e-02 ▁▁▁▇▁
numeric SE 0 1.0000000 NA NA NA NA NA 2.382100e-03 2.297800e-03 4.6620e-04 6.782000e-04 1.249800e-03 3.423300e-03 1.158300e-02 ▇▂▁▁▁
numeric PVAL 0 1.0000000 NA NA NA NA NA 4.691830e-01 2.984344e-01 0.0000e+00 2.036601e-01 4.597302e-01 7.279692e-01 1.000000e+00 ▇▆▆▆▆
numeric PVAL_ztest 0 1.0000000 NA NA NA NA NA 4.691825e-01 2.984347e-01 0.0000e+00 2.036545e-01 4.597290e-01 7.279725e-01 1.000000e+00 ▇▆▆▆▆
numeric AF 0 1.0000000 NA NA NA NA NA 1.908103e-01 2.544048e-01 1.0000e-03 7.431600e-03 6.004000e-02 2.953200e-01 9.989990e-01 ▇▂▁▁▁
numeric AF_reference 569171 0.9581059 NA NA NA NA NA 1.963399e-01 2.471029e-01 0.0000e+00 5.591000e-03 8.426520e-02 3.081070e-01 1.000000e+00 ▇▂▁▁▁
numeric N 0 1.0000000 NA NA NA NA NA 3.425900e+05 0.000000e+00 3.4259e+05 3.425900e+05 3.425900e+05 3.425900e+05 3.425900e+05 ▁▁▇▁▁

Head and tail

CHROM POS ID REF ALT EFFECT SE PVAL PVAL_ztest AF AF_reference N
1 692794 rs530212009 CA C -0.0010502 0.0009930 0.2902398 0.2902412 0.1105100 0.1894970 342590
1 693731 rs12238997 A G -0.0008560 0.0009379 0.3614099 0.3614077 0.1157900 0.1417730 342590
1 707522 rs371890604 G C -0.0012414 0.0010548 0.2392599 0.2392332 0.0972460 0.1293930 342590
1 717587 rs144155419 G A -0.0025836 0.0025190 0.3050598 0.3050589 0.0156520 0.0045926 342590
1 723329 rs189787166 A T 0.0025513 0.0074139 0.7307604 0.7307531 0.0017373 0.0003994 342590
1 730087 rs148120343 T C -0.0013208 0.0013070 0.3122497 0.3122278 0.0564170 0.0127796 342590
1 731718 rs142557973 T C -0.0010185 0.0008895 0.2522302 0.2522093 0.1216800 0.1543530 342590
1 732032 rs61770163 A C -0.0010348 0.0009492 0.2756398 0.2756283 0.1210900 0.1555510 342590
1 734349 rs141242758 T C -0.0009666 0.0008900 0.2774400 0.2774388 0.1209100 0.1525560 342590
1 740284 rs61770167 C T 0.0055796 0.0040825 0.1717200 0.1717157 0.0057552 0.0023962 342590
CHROM POS ID REF ALT EFFECT SE PVAL PVAL_ztest AF AF_reference N
23 154923311 rs141127553 C T -0.0007009 0.0010279 0.4953099 0.4953299 0.056212 0.0309934 342590
23 154923374 rs111332691 T A 0.0004043 0.0011284 0.7201401 0.7201292 0.044873 0.0116556 342590
23 154925045 rs509981 C T 0.0001697 0.0005436 0.7549705 0.7549655 0.245650 0.3634440 342590
23 154925895 rs538470 C T 0.0002377 0.0005561 0.6690507 0.6690450 0.241980 0.3634440 342590
23 154927581 rs644138 G A -0.0000526 0.0005112 0.9180301 0.9180293 0.302250 0.4635760 342590
23 154929412 rs557132 C T 0.0001561 0.0005438 0.7740197 0.7740166 0.245510 0.3568210 342590
23 154929637 rs35185538 CT C -0.0001491 0.0005676 0.7927806 0.7927755 0.229750 0.3011920 342590
23 154929952 rs4012982 CAA C 0.0002438 0.0005719 0.6698507 0.6698468 0.239490 0.3165560 342590
23 154930230 rs781880 A G 0.0001401 0.0005437 0.7966501 0.7966511 0.245910 0.3618540 342590
23 154930487 rs781879 T A 0.0000440 0.0018634 0.9811400 0.9811435 0.019562 0.1263580 342590

bcf preview

1   692794  rs530212009 CA  C   .   PASS    AF=0.11051  ES:SE:LP:AF:SS:ID   -0.0010502:0.00099301:0.537243:0.11051:342590:1_692794_CA_C
1   693731  rs12238997  A   G   .   PASS    AF=0.11579  ES:SE:LP:AF:SS:ID   -0.00085599:0.00093788:0.442:0.11579:342590:rs12238997
1   707522  rs371890604 G   C   .   PASS    AF=0.097246 ES:SE:LP:AF:SS:ID   -0.0012414:0.0010548:0.62113:0.097246:342590:rs371890604
1   717587  rs144155419 G   A   .   PASS    AF=0.015652 ES:SE:LP:AF:SS:ID   -0.0025836:0.002519:0.515615:0.015652:342590:rs144155419
1   723329  rs189787166 A   T   .   PASS    AF=0.0017373    ES:SE:LP:AF:SS:ID   0.0025513:0.0074139:0.136225:0.0017373:342590:rs189787166
1   730087  rs148120343 T   C   .   PASS    AF=0.056417 ES:SE:LP:AF:SS:ID   -0.0013208:0.001307:0.505498:0.056417:342590:rs148120343
1   731718  rs58276399  T   C   .   PASS    AF=0.12168  ES:SE:LP:AF:SS:ID   -0.0010185:0.00088952:0.598203:0.12168:342590:rs58276399
1   732032  rs61770163  A   C   .   PASS    AF=0.12109  ES:SE:LP:AF:SS:ID   -0.0010348:0.00094919:0.559658:0.12109:342590:rs61770163
1   734349  rs141242758 T   C   .   PASS    AF=0.12091  ES:SE:LP:AF:SS:ID   -0.00096661:0.00088999:0.556831:0.12091:342590:rs141242758
1   740284  rs61770167  C   T   .   PASS    AF=0.0057552    ES:SE:LP:AF:SS:ID   0.0055796:0.0040825:0.765179:0.0057552:342590:rs61770167
1   742813  rs112573343 C   T   .   PASS    AF=0.0018623    ES:SE:LP:AF:SS:ID   0.014839:0.0077356:1.25899:0.0018623:342590:rs112573343
1   749963  rs529266287 T   TAA .   PASS    AF=0.86981  ES:SE:LP:AF:SS:ID   0.00043576:0.00087745:0.207994:0.86981:342590:rs529266287
1   750230  rs190826124 G   C   .   PASS    AF=0.001514 ES:SE:LP:AF:SS:ID   -0.0026527:0.0079926:0.130786:0.001514:342590:rs190826124
1   751343  rs28544273  T   A   .   PASS    AF=0.12287  ES:SE:LP:AF:SS:ID   -0.00073596:0.00086892:0.401199:0.12287:342590:rs28544273
1   751488  rs200141114 G   GA  .   PASS    AF=0.14269  ES:SE:LP:AF:SS:ID   -0.00068143:0.00085881:0.369054:0.14269:342590:rs200141114
1   751756  rs28527770  T   C   .   PASS    AF=0.12298  ES:SE:LP:AF:SS:ID   -0.00067992:0.0008677:0.363231:0.12298:342590:rs28527770
1   753405  rs3115860   C   A   .   PASS    AF=0.87097  ES:SE:LP:AF:SS:ID   0.00052202:0.00084566:0.269985:0.87097:342590:rs3115860
1   753425  rs3131970   T   C   .   PASS    AF=0.87553  ES:SE:LP:AF:SS:ID   0.00050323:0.00085959:0.253163:0.87553:342590:rs3131970
1   753541  rs2073813   G   A   .   PASS    AF=0.12856  ES:SE:LP:AF:SS:ID   -0.00076771:0.00084774:0.437529:0.12856:342590:rs2073813
1   754105  rs12184325  C   T   .   PASS    AF=0.0363   ES:SE:LP:AF:SS:ID   -0.00049646:0.0015394:0.126633:0.0363:342590:rs12184325
1   754182  rs3131969   A   G   .   PASS    AF=0.87056  ES:SE:LP:AF:SS:ID   0.00060412:0.00084478:0.323736:0.87056:342590:rs3131969
1   754192  rs3131968   A   G   .   PASS    AF=0.87067  ES:SE:LP:AF:SS:ID   0.00061755:0.00084517:0.332566:0.87067:342590:rs3131968
1   754334  rs3131967   T   C   .   PASS    AF=0.87056  ES:SE:LP:AF:SS:ID   0.00061049:0.00084475:0.328022:0.87056:342590:rs3131967
1   754433  rs150578204 G   A   .   PASS    AF=0.0050485    ES:SE:LP:AF:SS:ID   -0.0019496:0.0043332:0.185246:0.0050485:342590:rs150578204
1   754458  rs142682604 G   T   .   PASS    AF=0.0050155    ES:SE:LP:AF:SS:ID   -0.0018612:0.0043447:0.174977:0.0050155:342590:rs142682604
1   755435  rs184270342 T   G   .   PASS    AF=0.0055515    ES:SE:LP:AF:SS:ID   0.0088839:0.0042134:1.45603:0.0055515:342590:rs184270342
1   755890  rs3115858   A   T   .   PASS    AF=0.87065  ES:SE:LP:AF:SS:ID   0.00054477:0.00084329:0.285436:0.87065:342590:rs3115858
1   756434  rs61768170  G   C   .   PASS    AF=0.12591  ES:SE:LP:AF:SS:ID   -0.00070372:0.00086041:0.383609:0.12591:342590:rs61768170
1   756604  rs3131962   A   G   .   PASS    AF=0.87022  ES:SE:LP:AF:SS:ID   0.00055813:0.00084129:0.294941:0.87022:342590:rs3131962
1   757640  rs3115853   G   A   .   PASS    AF=0.8695   ES:SE:LP:AF:SS:ID   0.00067951:0.00084051:0.377962:0.8695:342590:rs3115853
1   757734  rs4951929   C   T   .   PASS    AF=0.87037  ES:SE:LP:AF:SS:ID   0.00057302:0.00084199:0.304387:0.87037:342590:rs4951929
1   757936  rs4951862   C   A   .   PASS    AF=0.87037  ES:SE:LP:AF:SS:ID   0.00057237:0.00084205:0.303923:0.87037:342590:rs4951862
1   758144  rs3131956   A   G   .   PASS    AF=0.87038  ES:SE:LP:AF:SS:ID   0.00057877:0.00084208:0.308132:0.87038:342590:rs3131956
1   758626  rs3131954   C   T   .   PASS    AF=0.87082  ES:SE:LP:AF:SS:ID   0.00057299:0.00084421:0.303373:0.87082:342590:rs3131954
1   759293  rs10157329  T   A   .   PASS    AF=0.098794 ES:SE:LP:AF:SS:ID   -0.00077586:0.00098113:0.367472:0.098794:342590:rs10157329
1   759600  rs545998451 AGT A   .   PASS    AF=0.0064352    ES:SE:LP:AF:SS:ID   0.0063563:0.0038081:1.02188:0.0064352:342590:1_759600_AGT_A
1   759837  rs3115851   T   A   .   PASS    AF=0.87471  ES:SE:LP:AF:SS:ID   0.00058013:0.00085674:0.302492:0.87471:342590:rs3115851
1   761732  rs2286139   C   T   .   PASS    AF=0.86412  ES:SE:LP:AF:SS:ID   0.00066321:0.0008403:0.366562:0.86412:342590:rs2286139
1   761752  rs1057213   C   T   .   PASS    AF=0.8695   ES:SE:LP:AF:SS:ID   0.00069861:0.00084832:0.386994:0.8695:342590:rs1057213
1   762273  rs3115849   G   A   .   PASS    AF=0.86644  ES:SE:LP:AF:SS:ID   0.00057901:0.00084849:0.305404:0.86644:342590:rs3115849
1   762485  rs12095200  C   A   .   PASS    AF=0.098728 ES:SE:LP:AF:SS:ID   -0.00067227:0.0010158:0.294068:0.098728:342590:rs12095200
1   762589  rs3115848   G   C   .   PASS    AF=0.87162  ES:SE:LP:AF:SS:ID   0.00063164:0.0008582:0.335621:0.87162:342590:rs3115848
1   762592  rs3131950   C   G   .   PASS    AF=0.87162  ES:SE:LP:AF:SS:ID   0.00063177:0.0008582:0.335697:0.87162:342590:rs3131950
1   762601  rs3131949   T   C   .   PASS    AF=0.87162  ES:SE:LP:AF:SS:ID   0.00063314:0.00085822:0.33661:0.87162:342590:rs3131949
1   762632  rs3131948   T   A   .   PASS    AF=0.87199  ES:SE:LP:AF:SS:ID   0.00064146:0.0008587:0.341941:0.87199:342590:rs3131948
1   764191  rs7515915   T   G   .   PASS    AF=0.1255   ES:SE:LP:AF:SS:ID   -0.00079921:0.00085929:0.45305:0.1255:342590:rs7515915
1   766007  rs61768174  A   C   .   PASS    AF=0.1054   ES:SE:LP:AF:SS:ID   -0.00083199:0.00093563:0.427268:0.1054:342590:rs61768174
1   766105  rs2519015   T   A   .   PASS    AF=0.85546  ES:SE:LP:AF:SS:ID   0.00067079:0.00083996:0.372102:0.85546:342590:rs2519015
1   767393  rs538667473 A   C   .   PASS    AF=0.0016562    ES:SE:LP:AF:SS:ID   0.0047082:0.0074326:0.278659:0.0016562:342590:rs538667473
1   768116  rs376645387 A   AGTTTT  .   PASS    AF=0.83824  ES:SE:LP:AF:SS:ID   -1.7472e-05:0.00082702:0.00738463:0.83824:342590:rs376645387